[adegenet-commits] r617 - pkg/man

[noreply at r-forge.r-project.org]

Author: jombart
Date: 2010-05-10 16:03:58 +0200 (Mon, 10 May 2010)
New Revision: 617

Modified:
   pkg/man/seqTrack.Rd
Log:
not finished yet, but documented args for the main function.


Modified: pkg/man/seqTrack.Rd
===================================================================
--- pkg/man/seqTrack.Rd	2010-05-10 13:29:13 UTC (rev 616)
+++ pkg/man/seqTrack.Rd	2010-05-10 14:03:58 UTC (rev 617)
@@ -16,18 +16,21 @@
 \alias{coerce,seqTrack,graphNEL-method}
 \title{SeqTrack algorithm for reconstructing genealogies}
 \description{
-  The SeqTrack algorithm aims at reconstructing genealogies of sampled
-  haplotypes or genotypes for which a sampling date is
-  available. Contrary to phylogenetics which aims at reconstructing
-  hypothetical, unbserved most recent common ancestors (MRCA), SeqTrack
-  considers that both ancestors and descendents are sampled together.
+  The SeqTrack algorithm [1] aims at reconstructing genealogies of sampled
+  haplotypes or genotypes for which a collection date is
+  available. Contrary to phylogenetic methods which aims at reconstructing
+  hypothetical ancestors for observed sequences, SeqTrack
+  considers that ancestors and descendents are sampled together, and
+  therefore infers ancestry relationships among the sampled sequences.
 
   This approach proved more efficient than phylogenetic approaches for
   reconstructing transmission trees in densely sampled disease outbreaks
   [1]. This implementation defines a generic function \code{seqTrack}
+  with methods for specific object classes.
 
 }
 \usage{
+seqTrack(\ldots)
 
 \method{seqTrack}{matrix}(x, x.names, x.dates, best = c("min", "max"), prox.mat = NULL, 
     mu = NULL, haplo.length = NULL,  \dots)
@@ -38,11 +41,34 @@
     mu = NULL, seq.length = NULL, col.pal = heat.colors, plot = TRUE, \dots)
 }
 \arguments{
-  \item{seq.names}{}
-  \item{seq.dates}{}
-  \item{W}{}
-  \item{optim}{}
-  \item{x}{}
+  \item{x}{for seqTrack, a matrix giving weights to pairs of ancestries such that
+    x[i,j] is the weight of 'i ancestor of j'. For plotSeqTrack, a
+    seqTrack object.}
+  \item{seq.names}{a character vector giving the labels of the haplotypes/genotypes}
+  \item{seq.dates}{a vector of collection dates for the sampled
+    haplotypes/genotypes. Dates must have the POSIXct format. See
+    \code{details} or \code{?as.POSIXct} for more information.}
+  \item{best}{a character string matching 'min' or 'max', indicating
+    whether genealogies should minimize or maximize the sum of weights
+    of ancestries.}
+  \item{prox.mat}{an optional matrix of proximities between
+    haplotypes/genotypes used to resolve ties in the choice of
+    ancestors, by picking up the 'closest' ancestor amongst possible
+    ancestors, in the sense of \code{prox.mat}. \code{prox.mat[i,j]}
+    must indicate a proximity for the relationship 'i ancestor to
+    j'. For instance, if \code{prox.mat} contains spatial proximities,
+    then \code{prox.mat[i,j]} gives a measure of how easy it is to
+    migrate from location 'i' to 'j'.
+  }
+  \item{mu}{(optional) a mutation rate, per site and per day. When 'x'
+    contains numbers of mutations, used to resolve ties using a maximum
+    likelihood approach (requires \code{haplo.length} to be provided).}
+ \item{haplo.length}{(optional) the length of analysed sequences in
+    number of nucleotides. When 'x' contains numbers of mutations, used
+    to resolve ties using a maximum likelihood approach (requires
+    \code{haplo.length} to be provided).}
+  
+  
   \item{xy}{}
   \item{useArrows}{}
   \item{col}{}
@@ -50,8 +76,23 @@
   \item{add}{}
   \item{\dots}{}
   \item{}{}
+  \item{}{}
+  \item{}{}
+  \item{}{}
+  \item{}{}
+  \item{}{}
+  \item{}{}
+  \item{}{}
+  \item{}{}
+  \item{}{}
+  \item{}{}
+  \item{}{}
+  \item{}{}
+  \item{}{}
 }
-\author{Thibaut Jombart \email{t.jombart at imperial.ac.uk}}
+\author{
+  Thibaut Jombart \email{t.jombart at imperial.ac.uk}
+}
 \references{
   Jombart T, Eggo R, Dodd P, Balloux F (accepted) Reconstructing disease
   outbreaks from genetic data: a graph approach. Heredity.